Automated network planning for terrestrial wireless communication networks typically involves the use of algorithms that simulate radio frequency (RF) signal propagation and rely upon models of terrestrial communication towers, population data, and/or existing connectivity data to determine where to place new terrestrial communication towers. However, communication networks projected from high altitude platforms (HAPs), such as networks in which communication nodes are embodied as aerial vehicles floating in the atmosphere, are subject to technical challenges not faced by terrestrial networks and unaddressed by traditional network planning approaches. For instance, in HAP-based networks the communication nodes are subject to environmental influence, such as stratospheric winds, move vertically and laterally relative to the earth, and thus have a highly dynamic state. Additionally, the cost of providing service via an HAP-based communication network in a region depends on the navigability of nodes through the atmosphere in and around that region, and the navigability varies over time based upon season, weather, and/or other factors. Such a cost is also unaddressed by traditional network planning approaches. In view of the foregoing, it would be beneficial to have improved systems and methods for planning communication networks projected from HAPs.